• Corpus ID: 231879744

Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent

  title={Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent},
  author={Rishav Chourasia and Jiayuan Ye and R. Shokri},
We model the dynamics of privacy loss in Langevin diffusion and extend it to the noisy gradient descent algorithm: we compute a tight bound on Rényi differential privacy and the rate of its change throughout the learning process. We prove that the privacy loss converges exponentially fast. This significantly improves the prior privacy analysis of differentially private (stochastic) gradient descent algorithms, where (Rényi) privacy loss constantly increases over the training iterations. Unlike… 

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